Introduction
Universal Dependencies (UD) is a project that is developing cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on an evolution of (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008). The general philosophy is to provide a universal inventory of categories and guidelines to facilitate consistent annotation of similar constructions across languages, while allowing language-specific extensions when necessary.
What is needed for UD to be successful?
The secret to understanding the design and current success of UD is to realize that the design is a very subtle compromise between approximately 6 things:
- UD needs to be satisfactory on linguistic analysis grounds for individual languages.
- UD needs to be good for linguistic typology, i.e., providing a suitable basis for bringing out cross-linguistic parallelism across languages and language families.
- UD must be suitable for rapid, consistent annotation by a human annotator.
- UD must be suitable for computer parsing with high accuracy.
- UD must be easily comprehended and used by a non-linguist, whether a language learner or an engineer with prosaic needs for language processing. We refer to this as seeking a habitable design, and it leads us to favor traditional grammar notions and terminology.
- UD must support well downstream language understanding tasks (relation extraction, reading comprehension, machine translation, …).
It’s easy to come up with a proposal that improves UD on one of these dimensions. The interesting and difficult part is to improve UD while remaining sensitive to all these dimensions.
History
The Stanford dependencies were originally developed in 2005 as a backend to the Stanford parser to help in Recognizing Textual Entailment systems, then eventually emerged as the de facto standard for dependency analysis of English, and have since been adapted to a number of different languages (Chang et al., 2009, Bosco et al., 2013, Haverinen et al., 2013, Seraji et al., 2013, Tsarfaty, 2013, Lipenkova and Souček 2014). The Google universal tag set grew out of the cross-linguistic error analysis based on the CoNLL-X shared task data by McDonald and Nivre (2007), was initially used for unsupervised part-of-speech tagging by Das and Petrov (2011), and has since been adopted as a widely used standard for mapping diverse tagsets to a common standard. The Interset (Zeman, 2008) started as a tool for conversion between morphosyntactic tagsets of multiple languages. It dates back to 2006 when it was used in the first experiments with cross-lingual delexicalized parser adaptation (Zeman and Resnik, 2008). It was later employed as the morphological layer in HamleDT (Zeman et al., 2014) – a project that brings treebanks of many languages under a common annotation scheme.
The first attempt to combine Stanford dependencies and Google universal tags into a universal annotation scheme was the Universal Dependency Treebank (UDT) project (McDonald et al., 2013), which released treebanks for 6 languages in 2013 and 11 languages in 2014, and the first proposal for incorporating morphology was made by Tsarfaty (2013). The second version of HamleDT (Rosa et al., 2014) provided Stanford/Google annotation for 30 languages in 2014. This was followed by the development of universal Stanford dependencies (USD) (de Marneffe et al., 2014). The new Universal Dependencies is the result of merging all these initiatives into a single coherent framework, based on universal Stanford dependencies, an extended version of the Google universal tagset, a revised subset of the Interset feature inventory, and a revised version of the CoNLL-X format (called CoNLL-U).
The first version of the new guidelines, released in October 2014, introduced a somewhat extended universal part-of-speech tag set. This set makes some distinctions that were missing in the original proposal, but were perceived to be of importance by many, and clarifies the definition of categories. As a result of this work, universal POS categories have substantive definitions and are not necessarily just equivalence classes of categories in underlying language-particular treebanks. Hence, work to convert to UD POS tags often requires context-sensitive rules, or some hand correction. The UD morphological features aim to provide a stripped down basic set of features which are most crucial for analysis and are widespread across languages. The dependency representation of UD evolves out of Stanford Dependencies (SD), which itself follows ideas of grammatical relations-focused description that can be found in many linguistic frameworks. That is, it is centrally organized around notions of subject, object, clausal complement, noun determiner, noun modifier, etc. The goal of the new universal version was to add or refine relations to better accommodate the grammatical structures of typologically different languages and to clean up some of the quirkier and more English-specific features of the original version. Hence, the new taxonomy has less relations than the original SD.
Project organization
UD is an open collaboration with many project members. The administrative structure is kept at a minimum and currently consists of the following:
- The project is coordinated by Joakim Nivre (aka chief cat herder).
- Releases (including validation and documentation) are managed by Filip Ginter, Sampo Pyysalo and Dan Zeman.
- Universal guidelines are managed by a small group of core members, currently consisting of Marie de Marneffe, Filip Ginter, Yoav Goldberg, Jan Hajic, Chris Manning, Ryan McDonald, Joakim Nivre, Slav Petrov, Sampo Pyysalo, Natalia Silveira, Reut Tsarfaty and Dan Zeman.
- Language-specific guidelines and treebanks are maintained by each specific language team.
- Issues are raised on GitHub and resolved through discussion and voting.
UD-related publications
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Cristina Bosco, Simonetta Montemagni, Maria Simi. 2013. Converting Italian treebanks: Towards an Italian Stanford dependency treebank, In 7th Linguistic Annotation Workshop and Interoperability with Discourse.
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Pi-Chuan Chang, Huihsin Tseng, Dan Jurafsky, and Christopher D. Manning. 2009. Discriminative Reordering with Chinese Grammatical Relations Features. In Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation.
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Dipanjan Das, and Slav Petrov. 2011. Unsupervised part-of-speech tagging with bilingual graph-based projections In Proceedings of ACL.
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Katri Haverinen, Jenna Nyblom, Timo Viljanen, Veronika Laippala, Samuel Kohonen, Anna Missilä, Stina Ojala, Tapio Salakoski, and Filip Ginter. 2013. Building the essential resources for Finnish: the Turku Dependency Treebank. Language Resources and Evaluation. Volume 48, Issue 3, pp 493-531.
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Janna Lipenkova and Milan Souček. 2014. Converting Russian Dependency Treebank to Stanford Typed Dependencies Representation. In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, pp. 143-147.
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Marie-Catherine de Marneffe, Timothy Dozat, Natalia Silveira, Katri Haverinen, Filip Ginter, Joakim Nivre, and Christopher Manning. 2014. Universal Stanford Dependencies: A cross-linguistic typology. In Proceedings of LREC.
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Marie-Catherine de Marneffe, Bill MacCartney, and Christopher D. Manning. 2006. Generating typed dependency parses from phrase structure parses. In Proceedings of LREC.
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Marie-Catherine de Marneffe and Christopher D. Manning. 2008. The Stanford typed dependencies representation. In COLING Workshop on Cross-framework and Cross-domain Parser Evaluation.
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Ryan McDonald, and Joakim Nivre. 2007. Characterizing the errors of data-driven dependency parsing models. In Proceedings of EMNLP-CoNLL.
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Ryan McDonald, Joakim Nivre, Yvonne Quirmbach-Brundage, Yoav Goldberg, Dipanjan Das, Kuzman Ganchev, Keith Hall, Slav Petrov, Hao Zhang, Oscar Täckström, Claudia Bedini, Núria Bertomeu Castelló, and Jungmee Lee. 2013. Universal Dependency Annotation for Multilingual Parsing. In Proceedings of ACL. (home page)
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Joakim Nivre. 2014. Universal Dependencies for Swedish. In SLTC 2014.
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Joakim Nivre. 2015. Towards a Universal Grammar for Natural Language Processing. Computational Linguistics and Intelligent Text Processing.
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Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, Yoav Goldberg, Jan Hajič, Christopher D. Manning, Ryan McDonald, Slav Petrov, Sampo Pyysalo, Natalia Silveira, Reut Tsarfaty, Daniel Zeman. 2016. Universal Dependencies v1: A Multilingual Treebank Collection. In Proceedings of LREC.
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Slav Petrov, Dipanjan Das, and Ryan McDonald. 2012. A universal part-of-speech tagset. In Proceedings of LREC. (home page)
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Sampo Pyysalo, Jenna Kanerva, Anna Missilä, Veronika Laippala, and Filip Ginter. 2015. Universal Dependencies for Finnish. In Proceedings of Nodalida 2015.
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Rudolf Rosa, Jan Mašek, David Mareček, Martin Popel, Daniel Zeman, Zdeněk Žabokrtský. 2014. HamleDT 2.0: Thirty Dependency Treebanks Stanfordized. In Proceedings of LREC. (home page)
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Mojgan Seraji, Carina Jahani, Beáta Megyesi, and Joakim Nivre. 2013. A Persian treebank with Stanford typed dependencies. In Proceedings of LREC.
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Pavel Straňák, Jan Štěpánek. 2010. Representing Layered and Structured Data in the CoNLL-ST Format. In Proceedings of ICGL 2010.
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Reut Tsarfaty. 2013. A unified morpho-syntactic scheme of Stanford dependencies. In Proceedings of ACL.
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Daniel Zeman. 2008. Reusable Tagset Conversion Using Tagset Drivers. In Proceedings of LREC. (home page)
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Daniel Zeman. 2015. Slavic Languages in Universal Dependencies. In Slovko 2015: Natural Language Processing, Corpus Linguistics, E-learning. Bratislava, Slovakia. PDF
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Daniel Zeman, Ondřej Dušek, David Mareček, Martin Popel, Loganathan Ramasamy, Jan Štěpánek, Zdeněk Žabokrtský, and Jan Hajič. 2014. HamleDT: Harmonized multi-language dependency treebank. In Language Resources and Evaluation, DOI 10.1007/s10579-014-9275-2. (Extended version of paper from LREC 2012.)
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Daniel Zeman, and Philip Resnik. 2008. Cross-Language Parser Adaptation between Related Languages. In Proceedings of IJCNLP 2008 Workshop on NLP for Less Privileged Languages